The Experts below are selected from a list of 413133 Experts worldwide ranked by ideXlab platform
Dennis S. Bernstein - One of the best experts on this subject based on the ideXlab platform.
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adaptive control of nonminimum phase systems using shifted laurent series
International Journal of Control, 2017Co-Authors: Shicong Dai, Zhang Ren, Dennis S. BernsteinAbstract:ABSTRACTWe present a direct discrete-time output-feedback adaptive control algorithm for single-input, single-output systems that are possibly unstable and nonminimum phase. The plant Modeling Information is given by impulse response components, and the plant is modelled within the algorithm by a truncated shifted Laurent series. A shifted Laurent series is a Laurent series at a point different from the origin in the complex plane and about infinity. The shifted Laurent series is analysed, including its convergence and its relationship to other Laurent series. In particular, we provide a technique for constructing a truncated shifted Laurent series using impulse response components. Numerical examples show that retrospective cost adaptive control can achieve asymptotic command following for a class of exponentially unstable, nonminimum-phase systems.
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Aerodynamic-Free Adaptive Control of the NASA Generic Transport Model
2016Co-Authors: Frantisek M. Sobolic, Dennis S. BernsteinAbstract:Unanticipated and unknown changes in an aircraft’s aerodynamic stability derivatives may cause undesirable effects that render pre-designed control laws unsuitable for main-taining stability. Gradual changes in the stability derivatives may be due to icing on lifting surfaces, whereas structural damage may cause a sudden change. For this study, we use the nonlinear NASA Generic Transport Model (GTM) to investigate the ability of retrospective cost adaptive control (RCAC) to compensate for changes in the stability derivatives while maintaining steady level flight despite unknown variations in the aerodynamic Modeling Information. I
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Aircraft sensor fault detection using state and input estimation
2016 American Control Conference (ACC), 2016Co-Authors: Ahmad Ansari, Dennis S. BernsteinAbstract:This paper presents a method for detecting aircraft sensor faults using state and input estimation. We formulate the kinematics as a nonlinear state space system, which requires no Modeling Information, and thus is applicable to all aircraft. To illustrate the method, we investigate three fault-detection scenarios, namely, faulty pitot tube, angle-of-attack sensor, and accelerometers. We use the extended Kalman filter for pitot-tube and angle-of-attack sensor fault detection, and retrospective cost input estimation for accelerometer fault detection. For numerical illustration, we use the NASA Generic Transport Model to detect stuck, bias, drift, and deadzone sensor faults.
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adaptive control of uncertain hammerstein systems with hysteretic nonlinearities
Conference on Decision and Control, 2014Co-Authors: Mohammad Al Janaideh, Dennis S. BernsteinAbstract:We numerically investigate the sense in which an adaptive control law achieves internal model control of Hammerstein plants with Prandtl-Ishlinskii hysteresis. We apply retrospective cost adaptive control (RCAC) to a command-following problem for uncertain Hammerstein systems with hysteretic input nonlinearities. The only required Modeling Information of the linear plant is a single Markov parameter. Describing functions are used to determine whether the adaptive controller inverts the plant at the exogenous frequencies.
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a numerical investigation of phase and magnitude compensation in adaptive control of uncertain hammerstein systems with hysteretic nonlinearities
Advances in Computing and Communications, 2014Co-Authors: Mohammad Al Janaideh, Dennis S. BernsteinAbstract:We apply retrospective cost adaptive control (RCAC) to a command-following problem for uncertain Hammerstein systems with Duhem hysteresis nonlinearities. The only required Modeling Information of the linear plant is a single Markov parameter. We numerically investigate the sense in which RCAC achieves internal model control. The properties of the asymptotic controller are analyzed by using phase shift calculations.
Ling Shao - One of the best experts on this subject based on the ideXlab platform.
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learning compositional neural Information fusion for human parsing
International Conference on Computer Vision, 2019Co-Authors: Wenguan Wang, Zhijie Zhang, Jianbing Shen, Yanwei Pang, Ling ShaoAbstract:This work proposes to combine neural networks with the compositional hierarchy of human bodies for efficient and complete human parsing. We formulate the approach as a neural Information fusion framework. Our model assembles the Information from three inference processes over the hierarchy: direct inference (directly predicting each part of a human body using image Information), bottom-up inference (assembling knowledge from constituent parts), and top-down inference (leveraging context from parent nodes). The bottom-up and top-down inferences explicitly model the compositional and decompositional relations in human bodies, respectively. In addition, the fusion of multi-source Information is conditioned on the inputs, i.e., by estimating and considering the confidence of the sources. The whole model is end-to-end differentiable, explicitly Modeling Information flows and structures. Our approach is extensively evaluated on four popular datasets, outperforming the state-of-the-arts in all cases, with a fast processing speed of 23fps. Our code and results have been released to help ease future research in this direction.
Claire Beaumont - One of the best experts on this subject based on the ideXlab platform.
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elucidation of drug metabolite structural isomers using molecular Modeling coupled with ion mobility mass spectrometry
Analytical Chemistry, 2016Co-Authors: Eamonn Reading, Carol V. Robinson, Gj Dear, Jordi Munozmuriedas, Andrew Roberts, Claire BeaumontAbstract:Ion mobility-mass spectrometry (IM-MS) in combination with molecular Modeling offers the potential for small molecule structural isomer identification by measurement of their gas phase collision cross sections (CCSs). Successful application of this approach to drug metabolite identification would facilitate resource reduction, including animal usage, and may benefit other areas of pharmaceutical structural characterization including impurity profiling and degradation chemistry. However, the conformational behavior of drug molecules and their metabolites in the gas phase is poorly understood. Here the gas phase conformational space of drug and drug-like molecules has been investigated as well as the influence of protonation and adduct formation on the conformations of drug metabolite structural isomers. The use of CCSs, measured from IM-MS and molecular Modeling Information, for the structural identification of drug metabolites has also been critically assessed. Detection of structural isomers of drug meta...
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Elucidation of Drug Metabolite Structural Isomers Using Molecular Modeling Coupled with Ion Mobility Mass Spectrometry
2016Co-Authors: Eamonn Reading, Jordi Munoz-muriedas, Andrew D. Roberts, Gordon J. Dear, Carol V. Robinson, Claire BeaumontAbstract:Ion mobility-mass spectrometry (IM-MS) in combination with molecular Modeling offers the potential for small molecule structural isomer identification by measurement of their gas phase collision cross sections (CCSs). Successful application of this approach to drug metabolite identification would facilitate resource reduction, including animal usage, and may benefit other areas of pharmaceutical structural characterization including impurity profiling and degradation chemistry. However, the conformational behavior of drug molecules and their metabolites in the gas phase is poorly understood. Here the gas phase conformational space of drug and drug-like molecules has been investigated as well as the influence of protonation and adduct formation on the conformations of drug metabolite structural isomers. The use of CCSs, measured from IM-MS and molecular Modeling Information, for the structural identification of drug metabolites has also been critically assessed. Detection of structural isomers of drug metabolites using IM-MS is demonstrated and, in addition, a molecular Modeling approach has been developed offering rapid conformational searching and energy assessment of candidate structures which agree with experimental CCSs. Here it is illustrated that isomers must possess markedly dissimilar CCS values for structural differentiation, the existence and extent of CCS differences being ionization state and molecule dependent. The results present that IM-MS and molecular Modeling can inform on the identity of drug metabolites and highlight the limitations of this approach in differentiating structural isomers
Wenguan Wang - One of the best experts on this subject based on the ideXlab platform.
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learning compositional neural Information fusion for human parsing
International Conference on Computer Vision, 2019Co-Authors: Wenguan Wang, Zhijie Zhang, Jianbing Shen, Yanwei Pang, Ling ShaoAbstract:This work proposes to combine neural networks with the compositional hierarchy of human bodies for efficient and complete human parsing. We formulate the approach as a neural Information fusion framework. Our model assembles the Information from three inference processes over the hierarchy: direct inference (directly predicting each part of a human body using image Information), bottom-up inference (assembling knowledge from constituent parts), and top-down inference (leveraging context from parent nodes). The bottom-up and top-down inferences explicitly model the compositional and decompositional relations in human bodies, respectively. In addition, the fusion of multi-source Information is conditioned on the inputs, i.e., by estimating and considering the confidence of the sources. The whole model is end-to-end differentiable, explicitly Modeling Information flows and structures. Our approach is extensively evaluated on four popular datasets, outperforming the state-of-the-arts in all cases, with a fast processing speed of 23fps. Our code and results have been released to help ease future research in this direction.
Eamonn Reading - One of the best experts on this subject based on the ideXlab platform.
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elucidation of drug metabolite structural isomers using molecular Modeling coupled with ion mobility mass spectrometry
Analytical Chemistry, 2016Co-Authors: Eamonn Reading, Carol V. Robinson, Gj Dear, Jordi Munozmuriedas, Andrew Roberts, Claire BeaumontAbstract:Ion mobility-mass spectrometry (IM-MS) in combination with molecular Modeling offers the potential for small molecule structural isomer identification by measurement of their gas phase collision cross sections (CCSs). Successful application of this approach to drug metabolite identification would facilitate resource reduction, including animal usage, and may benefit other areas of pharmaceutical structural characterization including impurity profiling and degradation chemistry. However, the conformational behavior of drug molecules and their metabolites in the gas phase is poorly understood. Here the gas phase conformational space of drug and drug-like molecules has been investigated as well as the influence of protonation and adduct formation on the conformations of drug metabolite structural isomers. The use of CCSs, measured from IM-MS and molecular Modeling Information, for the structural identification of drug metabolites has also been critically assessed. Detection of structural isomers of drug meta...
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Elucidation of Drug Metabolite Structural Isomers Using Molecular Modeling Coupled with Ion Mobility Mass Spectrometry
2016Co-Authors: Eamonn Reading, Jordi Munoz-muriedas, Andrew D. Roberts, Gordon J. Dear, Carol V. Robinson, Claire BeaumontAbstract:Ion mobility-mass spectrometry (IM-MS) in combination with molecular Modeling offers the potential for small molecule structural isomer identification by measurement of their gas phase collision cross sections (CCSs). Successful application of this approach to drug metabolite identification would facilitate resource reduction, including animal usage, and may benefit other areas of pharmaceutical structural characterization including impurity profiling and degradation chemistry. However, the conformational behavior of drug molecules and their metabolites in the gas phase is poorly understood. Here the gas phase conformational space of drug and drug-like molecules has been investigated as well as the influence of protonation and adduct formation on the conformations of drug metabolite structural isomers. The use of CCSs, measured from IM-MS and molecular Modeling Information, for the structural identification of drug metabolites has also been critically assessed. Detection of structural isomers of drug metabolites using IM-MS is demonstrated and, in addition, a molecular Modeling approach has been developed offering rapid conformational searching and energy assessment of candidate structures which agree with experimental CCSs. Here it is illustrated that isomers must possess markedly dissimilar CCS values for structural differentiation, the existence and extent of CCS differences being ionization state and molecule dependent. The results present that IM-MS and molecular Modeling can inform on the identity of drug metabolites and highlight the limitations of this approach in differentiating structural isomers
